The long-standing debate within the cryptocurrency sector over whether quantum computing could threaten blockchain networks such as Bitcoin and Ethereum is taking on renewed urgency. Industry experts now believe that artificial intelligence (AI) may be speeding up the arrival of quantum breakthroughs, prompting concerns about the future of digital security.
Specialists working in blockchain protection and post-quantum cryptography say the intersection of AI and quantum computing is reshaping cybersecurity. AI is increasingly being used both by attackers seeking vulnerabilities and by developers strengthening defenses. At the same time, it is helping advance quantum computing research at a faster pace.
“The security landscape of the future is going to be different,” said Alex Pruden, CEO of Project Eleven, a company focused on quantum-resistant infrastructure for crypto.
“Between quantum and AI, we’re going to go into a world where security, and this is more broadly than just crypto, you simply cannot count on the way you’ve always done things,” Pruden said.
The growing concern follows warnings from technology companies and researchers suggesting that quantum computers capable of breaking current cryptographic systems could arrive sooner than expected. While experts continue to debate the exact timeline, many agree that AI could significantly accelerate progress in the field.
“AI is definitely being used to accelerate the development of quantum computing,” Pruden said. Researchers are already using machine learning systems to optimize quantum error correction, one of the field’s biggest engineering bottlenecks.
Illia Polosukhin, co-founder of NEAR Protocol and a former Google AI researcher, noted that AI has been enhancing scientific innovation for years.
“AI is becoming more and more of an accelerator,” Polosukhin said. “The rate of research is going to accelerate from here, and we have already seen progress that people didn’t expect would come this early.”
Reflecting on his experience at Google in 2016, Polosukhin explained that machine learning was already contributing to the discovery of new materials. “It might be that the next generation quantum computer will be built with AI and quantum computers of this generation,” he said. “It’s feeding into itself.”
Security experts are increasingly focused on a strategy known as “harvest now, decrypt later,” where sensitive encrypted information is collected today in anticipation of future quantum systems being able to decode it.
“If I know quantum computers are coming in a couple of years, I will start trying to capture all possible data that’s going around,” Polosukhin said.
“Everything we’re putting on the internet, if you’re identifiable as a person of interest, you can assume will be decrypted in two years,” he added. “It’s most likely happening already.”
For the cryptocurrency industry, the risks are particularly significant. Most blockchain networks rely on elliptic curve cryptography, a security standard widely used across the internet. A sufficiently advanced quantum computer could potentially derive private keys from public keys, exposing wallets and digital assets to theft.
However, experts argue that the real challenge lies not in quantum computing alone but in its combination with AI, creating an ongoing cybersecurity arms race.
Artificial intelligence is becoming increasingly capable of identifying coding weaknesses, software flaws, and security vulnerabilities. According to Pruden, these advances may increase the frequency and sophistication of cyberattacks.
“I would expect the advent of AI to accelerate… even more hacks,” Pruden said. “You have these AI models that are able to find either implementation bugs in the underlying cryptography or increasingly, I think, break the cryptography itself.”
At the same time, developers are leveraging AI to improve software security through code reviews, testing, and formal verification processes.
“AI can help with formal verification of post-quantum systems,” Pruden said. “That theoretically makes them more secure.”
Researchers believe this evolving environment means security can no longer be treated as a static framework that receives occasional updates. Instead, digital systems may require constant adaptation to stay resilient.
“Nothing is going to be as static as it’s been in the future,” Pruden said. “Either a quantum computer comes online to break some fundamental assumption, or AI gets smart enough to break that assumption too.”
This shift is already influencing blockchain ecosystems. Networks including Ethereum, Zcash, Solana, Ripple, and NEAR are exploring or implementing strategies designed to support post-quantum security.
NEAR recently revealed plans to integrate post-quantum cryptography into its account architecture, enabling users to switch cryptographic methods without moving assets to new wallets.
“Back in 2018, when we were designing [NEAR], we were like: ‘Hey, quantum will come, we should have an easy way to do it,’” Polosukhin said.
Despite growing momentum, the transition remains challenging. Current post-quantum cryptographic solutions often require more computational resources and larger data sizes than existing standards.
“The cryptography that’s currently standardized for post-quantum is very big and slow,” Polosukhin said.
According to researchers, the broader impact of AI and quantum computing is forcing a rethink of one of the digital era’s core assumptions—that encryption can remain secure for extended periods. As technology evolves, cybersecurity may increasingly depend on continuous upgrades and adaptive protection mechanisms rather than long-term static safeguards.